From a Formalized Parallel Action Language to Its Efficient Code Generation
Ivan Llopard, Christian Fabre, Albert Cohen · ACM Transactions on Embedded Computing Systems · 2017
Modeling languages propose convenient abstractions and transformations to handle the complexity of today’s embedded systems. Based on the formalism of the Hierarchical State Machine, they enable the expression of hierarchical control parallelism. However, they face two important challenges when it comes to modeling data-intensive applications: no unified approach that also accounts for data-parallel actions and no effective code optimization and generation flows. We propose a modeling language extended with parallel action semantics and hierarchical indexed-state machines suitable for computationally intensive applications. Together with its formal semantics, we present an optimizing model compiler aiming for the generation of efficient data-parallel implementations.